Monthly Active Users (MAU)
The number of unique users who interact meaningfully with a product or service in a given 30-day period — the standard engagement metric for subscription, SaaS, and app businesses, distinct from total subscribers or registered accounts.
Monthly Active Users (MAU) measures unique users who took a defined "active" action within a 30-day window. The definition of "active" varies by business model — for a subscription brand it might mean a logged-in session or a delivery event, for a SaaS product it might mean a feature interaction. The shared idea is that MAU separates engaged users from passive subscribers and dormant accounts.
For e-commerce subscription brands, MAU is the bridge between subscription count and actual product engagement. A brand with 10,000 subscribers and only 6,000 MAU has a 60% active rate — meaning 4,000 subscribers are paying without engaging, a strong signal of impending involuntary or voluntary churn. Tracking MAU alongside subscriber count gives an earlier warning than churn rate, which is a lagging indicator.
The most useful MAU derivative is the DAU/MAU ratio, often called the "stickiness ratio." A 50% DAU/MAU ratio means the average active user is in the product 15 days per month; a 10% ratio means they show up about 3 days per month. Consumer apps target stickiness ratios above 20%; B2B SaaS commonly sits around 40-60%; e-commerce subscriptions are usually 5-15% because purchase cadence is monthly or quarterly, not daily.
The most common MAU mistakes are: counting registered accounts instead of unique active users, using inconsistent active-action definitions across reports, and failing to segment MAU by acquisition cohort. Cohort-segmented MAU reveals whether engagement is degrading in newer cohorts before churn metrics catch up — a leading indicator that lets you intervene before the revenue impact materializes.
For brands that want to act on MAU, the sequence is: track MAU and DAU/MAU by cohort, identify the engagement actions that correlate with retention (often surfacing 1-2 "magic moment" actions in the first 30 days), build onboarding flows that drive new subscribers to those actions, and continuously measure whether onboarding interventions move the cohort-level MAU curve up over time.
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